Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines
In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes the signals from the faulty tu...
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| Formato: | Articulo |
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2022
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/155781 |
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I19-R120-10915-1557812023-08-02T20:04:08Z http://sedici.unlp.edu.ar/handle/10915/155781 Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines Marti Puig, Pere Cusidó, Jordi Lozano, Francisco J. Serra Serra, Moises Caiafa, Cesar Federico Solé Casals, Jordi 2022-10 2023-08-02T18:32:40Z en Ingeniería Astronomía wind turbine fault diagnosis renewable energy feature engineering normal behaviour models In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes the signals from the faulty turbine to decouple from the pattern. From this information, SCADA data is used to determine, firstly, how to derive reference signals describing this pattern and, secondly, to compare the evolution of different turbines with respect to this joint variation. This makes it possible to determine whether the behaviour of the assembly is correct, because they maintain the well-functioning patterns, or whether they are decoupled. The presented strategy is very effective and can provide important support for decision making in turbine maintenance and, in the near future, to improve the classification of signals for training supervised normality models. In addition to being a very effective system, it is a low computational cost strategy, which can add great value to the SCADA data systems present in wind farms. Instituto Argentino de Radioastronomía Articulo Articulo http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) application/pdf |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Ingeniería Astronomía wind turbine fault diagnosis renewable energy feature engineering normal behaviour models |
| spellingShingle |
Ingeniería Astronomía wind turbine fault diagnosis renewable energy feature engineering normal behaviour models Marti Puig, Pere Cusidó, Jordi Lozano, Francisco J. Serra Serra, Moises Caiafa, Cesar Federico Solé Casals, Jordi Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| topic_facet |
Ingeniería Astronomía wind turbine fault diagnosis renewable energy feature engineering normal behaviour models |
| description |
In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes the signals from the faulty turbine to decouple from the pattern. From this information, SCADA data is used to determine, firstly, how to derive reference signals describing this pattern and, secondly, to compare the evolution of different turbines with respect to this joint variation. This makes it possible to determine whether the behaviour of the assembly is correct, because they maintain the well-functioning patterns, or whether they are decoupled. The presented strategy is very effective and can provide important support for decision making in turbine maintenance and, in the near future, to improve the classification of signals for training supervised normality models. In addition to being a very effective system, it is a low computational cost strategy, which can add great value to the SCADA data systems present in wind farms. |
| format |
Articulo Articulo |
| author |
Marti Puig, Pere Cusidó, Jordi Lozano, Francisco J. Serra Serra, Moises Caiafa, Cesar Federico Solé Casals, Jordi |
| author_facet |
Marti Puig, Pere Cusidó, Jordi Lozano, Francisco J. Serra Serra, Moises Caiafa, Cesar Federico Solé Casals, Jordi |
| author_sort |
Marti Puig, Pere |
| title |
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| title_short |
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| title_full |
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| title_fullStr |
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| title_full_unstemmed |
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines |
| title_sort |
detection of wind turbine failures through cross-information between neighbouring turbines |
| publishDate |
2022 |
| url |
http://sedici.unlp.edu.ar/handle/10915/155781 |
| work_keys_str_mv |
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| _version_ |
1807220850143789056 |